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These data set sizes range from 47 to 1389 records.
The training set sizes were varied in a logarithmic scale.
The developed framework is tested against different data set sizes.
The queries are executed against different data set sizes.
In practical applications, the test set sizes should be varied.
For even set sizes, the exact null distribution of WRSS+ is simulated.
We also tested 38 different calibration set sizes varying from 10 to 380 samples.
Fig. 9 Reconstruction error for different training set sizes on the Intel-Berkeley dataset.
In case of large validation data set sizes LMO-CV tends to omit important variables [2].
For lager test data set sizes, LMO-CV was used in the outer loop.
The best cost values vary between 0.05 and 0.1 for the different training set sizes.
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